To the best of our knowledge, this is the first work exposing privacy and security vulnerabilities of radiometric fingerprints as well as devising practical methods to resolve them. Note that prior works such as [1]}, [2]} propose techniques for preventing the exposure of unencrypted fields (e.g., headers and payload information) to counter, for instance, reactive jamming attacks that can adapt to the rate of transmission. While the approach prevents data analysis and acquisition of transmission cues, it does not protect the radiometric fingerprint of the device. The following summarizes our main contributions:
(i) Showing vulnerabilities of recent CSI-based radiometric fingerprinting solutions [3]}, [4]}, [5]} to impersonation attacks (Section );
(ii) Proposing a method for injecting artificial noise to the fingerprint without impacting communication quality (Section ).
(iii) Designing RF-Scope, a benchmarking tool to assess the effectiveness of radiometric fingerprint obfuscation against statistical attacks (Section ). Specifically, RF-Scope is a maximum-likelihood-based estimator of the CSI, which we prove to be near-optimal through derivation of Cramer-Rao bounds (Appendix );
(iv) Devising RF-Veil, a fingerprint obfuscation framework that circumvents the privacy issues without impacting the communication quality (Section ).
(v) We prove the efficacy of our proposals, both analytically and experimentally.
